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verb WS8

*The author of this computation has been verified*
R Software Module: /rwasp_autocorrelation.wasp (opens new window with default values)
Title produced by software: (Partial) Autocorrelation Function
Date of computation: Thu, 03 Dec 2009 11:01:50 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/03/t1259863348hvk56sgawqbgau8.htm/, Retrieved Thu, 03 Dec 2009 19:02:30 +0100
 
BibTeX entries for LaTeX users:
@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2009/Dec/03/t1259863348hvk56sgawqbgau8.htm/},
    year = {2009},
}
@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Development Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2009},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
8.6 8.5 8.3 7.8 7.8 8 8.6 8.9 8.9 8.6 8.3 8.3 8.3 8.4 8.5 8.4 8.6 8.5 8.5 8.5 8.5 8.5 8.5 8.5 8.5 8.5 8.5 8.5 8.6 8.4 8.1 8 8 8 8 7.9 7.8 7.8 7.9 8.1 8 7.6 7.3 7 6.8 7 7.1 7.2 7.1 6.9 6.7 6.7 6.6 6.9 7.3 7.5 7.3 7.1 6.9 7.1
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.0212790.16210.435912
2-0.090104-0.68620.247656
3-0.425407-3.23980.000991
4-0.310889-2.36770.010628
5-0.008133-0.06190.475413
60.2213541.68580.048605
70.1236260.94150.175174
80.1525411.16170.125055
9-0.042904-0.32670.372517
10-0.055029-0.41910.338349
11-0.161714-1.23160.111539
120.1063170.80970.210716
13-0.187506-1.4280.079327
140.1567311.19360.118742
150.0986470.75130.227763
16-0.016774-0.12770.449395
170.0047250.0360.485708
18-0.114294-0.87040.193826
19-0.063868-0.48640.314256
200.0930110.70830.240783
210.0847030.64510.26071
220.0508470.38720.349998
23-0.034107-0.25970.397988
24-0.183153-1.39490.08419
25-0.106738-0.81290.209802
260.1657711.26250.105915
270.1446891.10190.137524
28-0.026088-0.19870.421604
29-0.059944-0.45650.32486
30-0.195996-1.49270.070473
310.0718150.54690.293264
320.1060890.80790.211211
330.1358841.03490.152514
340.0206830.15750.437692
35-0.064491-0.49110.312587
36-0.234607-1.78670.039605
37-0.059815-0.45550.325211
380.0340730.25950.398088
390.1270790.96780.168579
400.0795680.6060.273449
410.1436491.0940.13924
42-0.132921-1.01230.1578
43-0.005629-0.04290.482977
44-0.170166-1.29590.100064
45-0.064385-0.49030.312872
46-0.000524-0.0040.498415
470.169571.29140.100843
480.1310150.99780.161266
490.1146320.8730.193129
50-0.161718-1.23160.111533
51-0.158352-1.2060.116362
52-0.115562-0.88010.19122
530.12670.96490.169297
540.0504820.38450.351021
550.0840960.64050.2622
56-0.051075-0.3890.34936
57-0.017682-0.13470.446673
58NANANA
59NANANA
60NANANA


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0212790.16210.435912
2-0.090598-0.690.246481
3-0.425068-3.23720.000999
4-0.388598-2.95950.002228
5-0.206651-1.57380.060485
6-0.106797-0.81330.209674
7-0.277697-2.11490.019374
8-0.111382-0.84830.199891
9-0.073634-0.56080.288554
10-0.038554-0.29360.385049
11-0.161965-1.23350.111184
120.1727441.31560.096746
13-0.227007-1.72880.04458
140.0282840.21540.415104
150.1844761.40490.082688
16-0.062196-0.47370.318758
170.0136560.1040.458763
180.00860.06550.474003
190.0385720.29380.384998
200.0128310.09770.461248
210.1448331.1030.137288
220.0841910.64120.261967
230.0883920.67320.251756
24-0.148101-1.12790.132002
25-0.000331-0.00250.499
260.1113350.84790.199989
270.0240460.18310.427666
28-0.153684-1.17040.123309
29-0.155192-1.18190.121033
30-0.184409-1.40440.082763
31-0.093309-0.71060.240085
32-0.109832-0.83650.203165
330.0044380.03380.486575
340.0395610.30130.382136
350.0345690.26330.396639
36-0.043422-0.33070.371034
37-0.050437-0.38410.351147
38-0.02072-0.15780.437583
390.0177740.13540.446398
40-0.085692-0.65260.258292
410.0428720.32650.372609
42-0.07154-0.54480.293978
430.0041490.03160.487449
440.0148940.11340.455041
45-0.05694-0.43360.333077
46-0.14258-1.08590.141017
470.0125960.09590.461953
480.024850.18930.425278
49-0.033684-0.25650.399223
50-0.029819-0.22710.410574
510.0649140.49440.311456
520.0101980.07770.469181
530.0116720.08890.464737
540.0100050.07620.469763
55-0.081208-0.61850.269345
56-0.005368-0.04090.483766
570.046560.35460.362091
58NANANA
59NANANA
60NANANA
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2009/Dec/03/t1259863348hvk56sgawqbgau8/1wn2u1259863308.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Dec/03/t1259863348hvk56sgawqbgau8/1wn2u1259863308.ps (open in new window)


http://www.freestatistics.org/blog/date/2009/Dec/03/t1259863348hvk56sgawqbgau8/2vugx1259863308.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Dec/03/t1259863348hvk56sgawqbgau8/2vugx1259863308.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 2 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
 
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 2 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
 
R code (references can be found in the software module):
if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
par7 <- as.numeric(par7)
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('http://www.xycoon.com/basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 2:(par1+1)) {
a<-table.row.start(a)
a<-table.element(a,i-1,header=TRUE)
a<-table.element(a,round(myacf[i],6))
mytstat <- myacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('http://www.xycoon.com/basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,round(mypacf[i],6))
mytstat <- mypacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
 




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Software written by Ed van Stee & Patrick Wessa


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